Instructions to use Kry4ta1/Effecteraser-VOR-Inference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kry4ta1/Effecteraser-VOR-Inference with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kry4ta1/Effecteraser-VOR-Inference", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download src/videox_fun/data/__init__.py from Kry4ta1/Effecteraser-VOR-Inference: direct link, hf CLI and curl.
- Browser
- Download file 369 Bytes
-
https://huggingface.co/Kry4ta1/Effecteraser-VOR-Inference/resolve/main/src/videox_fun/data/__init__.py
- Command line
-
hf download hf://Kry4ta1/Effecteraser-VOR-Inference/src/videox_fun/data/__init__.py
-
curl -L -o __init__.py https://huggingface.co/Kry4ta1/Effecteraser-VOR-Inference/resolve/main/src/videox_fun/data/__init__.py
369 Bytes
| from .remove_dataset import ( | |
| RemoveTripletDataset, | |
| degrade_mask, | |
| derive_side_effect_mask, | |
| discover_video_triplets, | |
| muse_temporal_union, | |
| orientation_aware_size, | |
| ) | |
| __all__ = [ | |
| "RemoveTripletDataset", | |
| "degrade_mask", | |
| "derive_side_effect_mask", | |
| "discover_video_triplets", | |
| "muse_temporal_union", | |
| "orientation_aware_size", | |
| ] | |